US 6505131 B1 Abstract A digital signal processor for determining a property of a material flowing through a conduit. The digital signal processor of this invention receives signals from two pick-off sensor mounted at two different points along a flow tube at a first sample rate. The signals are converted to digital signals. The digital signals are decimated from a first sample rate to a desired sample rate. The frequency of the received signals is then determined from the digital signals at the desired sample rate.
Claims(26) 1. A method for processing signals received from a first pick-off sensor and a second pick-off sensor measuring vibrations of a conduit using a digital signal processor to output information about a material flowing through said conduit, said method comprising the steps of:
receiving samples of signals from said first pick-off sensor and said second pick-off sensor at a first sample rate;
decimating said samples from said first sample rate to a desired sample rate;
determining a frequency of vibration for said conduit at said first pick-off and at said second pick-off from said samples of said signals at said desired sample rate;
calculating a normalized frequency of said signals; and
demodulating said signals from said first pick-off sensor and said second pick-off sensor to translate said signals to a center frequency, wherein said step of demodulating comprises the steps of:
calculating a normalized pulsation of said normalized frequency of said signals; and
calculating dot products of said normalized pulsation and said signals from said first pick-off sensor and said second pick-off sensor to translate said signals to said center frequency.
2. The method of
demultiplexing said signals into I components and Q components;
integrating said I components;
integrating said Q components
multiplexing said I components and said Q components to produce digitally integrated signals; and
calculating a ratio between an amplitude of said signals and an amplitude of said digitally integrated signals to produce said normalized frequency of said signals.
3. The method of
applying said integrated Q components to a compensator responsive to said step of integrating prior to said step of multiplexing.
4. The method of
applying said integrated I components to a compensator responsive to said step of integrating prior to said step of multiplexing.
5. The method of
determining properties of said material flowing through said conduit responsive to determining said frequency of said signals from said first pick-off sensor and said signals from said second pick-off sensor.
6. The method of
7. The method of
8. The method of
modulating said normalized frequency of said signals; and
performing a complex demodulation of said signals using said modulated normalized frequency to determine said frequency.
9. The method of
decimating said demodulated signals;
performing a complex correlation of said signals to determine a phase difference between said signals.
10. The method of
performing a preliminary decimation from said first sample rate to an intermediate sample rate responsive to receiving said signals from said first and said second pickoff sensors.
11. The method of
demodulating said signals into an I component and a Q component; and
performing a secondary decimation of said samples of said signals from said intermediate sample rate to a final sample rate responsive to said demodulation of said signals.
12. The method of
determining a phase difference between said signals from said first pick-off sensor and said signals from said second pick-off sensor.
13. A product for directing a processor controlling an apparatus that has a vibrating conduit for measuring properties of a material flowing through said conduit to process signals received from a first pick-off sensor and a second pick-off sensor connected to said conduit, said product comprising:
instructions operational to perform
receiving samples of signals from said first and said second pick-off sensors at a first sample rate,
decimating said samples from said first sample rate to a desired sample rate,
determining a frequency of vibration for said conduit at said first pickoff sensor and at said second pick-off sensor from said samples of said signals at said desired sample rate,
calculating a normalized frequency of said signals, and
demodulating said signals from said first pick-off sensor and said second pick-off sensor to translate said signals to a center frequency, wherein said step of demodulating comprises the steps of:
calculating a normalized pulsation of said normalized frequency of said signals; and
calculating dot products of said normalized pulsation and said signals from said first pick-off sensor and said second pick-off sensor to translate said signals to said center frequency; and
a processor readable storage media for storing said instructions.
14. The product of
demultiplexing said signals into an I component and a Q component;
integrating said I component;
integrating said Q component;
multiplexing said I component and said Q component to produce digitally integrated signals; and
calculating a ratio between an amplitude of said signals and said digitally integrated signals to produce said normalized frequency of said signals.
15. The product of
applying said integrated Q component to a compensator responsive to said step of integrating prior to said step of multiplexing.
16. The product of
applying said integrated I component to a compensator responsive to said step of integrating prior to said step of multiplexing.
17. The product of
determining properties of said material flowing through said conduit responsive to determining said frequency of said signals from said first pick-off sensor and said signals from said second pick-off sensor.
18. The product of
19. The product of
20. The product of
modulating said normalized frequency of said signals; and
performing a complex demodulation of said signals using said modulated normalized frequency to determine said frequency.
21. The product of
decimating said demodulated signals;
performing a complex correlation of said signals to determine a phase difference between said signals.
22. The product of
23. The product of
demodulating said signals from an I component and a Q component; and
performing a secondary decimation of said samples of said signals from said intermediate sample rate to a final sampled rate responsive to said demodulation of said signals.
24. The product of
determining a phase difference between said signals from said first pick-off sensor and said signals from said second pick-off sensor.
25. The product of
26. A transmitter for a Coriolis flowmeter comprising:
a processing unit;
a memory storage media readable by said processing unit; and
processor readable instructions stored in said storage media for directing said processing unit to perform
receiving samples of signals from first and second pick-off sensors at a first sample rate,
decimating said samples from said first sample rate to a desired sample rate,
determining a frequency of vibration for said conduit at said first pick-off sensor and at said second pick-off sensor from said samples of said signals at said desired sample rate,
calculating a normalized frequency of said signals, and
demodulating said signals from said first pick-off sensor and said second pick-off sensor to translate said signals to a center frequency, wherein said step of demodulating comprises the steps of:
calculating a normalized pulsation of said normalized frequency of said signals; and
calculating dot products of said normalized pulsation and said signals from said first pick-off sensor and said second pick-off sensor to translate said signals to said center frequency.
Description This invention relates to a signal processor for an apparatus that measures properties of a material flowing through at least one vibrating conduit in the apparatus. More particularly, this invention relates to a digital signal processor for performing calculations to determine the frequencies of signals receive from pick-off sensors measuring the frequency of vibrations of the conduit. It is known to use Coriolis effect mass flowmeters to measure mass flow and other information for materials flowing through a conduit in the flowmeter. Exemplary Coriolis flowmeters are disclosed in U.S. Pat. Nos. 4,109,524 of Aug. 29, 1978, U.S. Pat. No. 4,491,025 of Jan. 1, 1985, and U.S. Pat. No. Re. 31,450 of Feb. 11, 1982, all to J. E. Smith et al. These flowmeters have one or more conduits of a straight or a curved configuration. Each conduit configuration in a Coriolis mass flowmeter has a set of natural vibration modes, which may be of a simple bending, torsional or coupled type. Each conduit is driven to oscillate at resonance in one of these natural modes. Material flows into the flowmeter from a connected pipeline on the inlet side of the flowmeter, is directed through the conduit or conduits, and exits the flowmeter through the outlet side of the flowmeter. The natural vibration modes of the vibrating, material filled system are defined in part by the combined mass of the conduits and the material flowing within the conduits. When there is no flow through the flowmeter, all points along the conduit oscillate due to an applied driver force with identical phase or small initial fixed phase offset which can be corrected. As material begins to flow, Coriolis forces cause each point along the conduit to have a different phase. The phase on the inlet side of the conduit lags the driver, while the phase on the outlet side of the conduit leads the driver. Pick-off sensors are placed on the conduit(s) to produce sinusoidal signals representative of the motion of the conduit(s). Signals outputted from the pick-off sensors are processed to determine the phase difference between the pick-off sensors. The phase difference between two pick-off sensor signals is proportional to the mass flow rate of material through the conduit(s). A Coriolis flowmeter has a transmitter which generates a drive signal to operate the driver and determines a mass flow rate and other properties of a material from signals received from the pick-off sensors. A conventional transmitter is made of analog circuitry which is designed to generate the drive signal and detect the signals from the pick-off sensors. Analog transmitters have been optimized over the years and have become relatively cheap to manufacture. It is therefore desirable to design Coriolis flowmeters that can use conventional transmitters. It is a problem that conventional transmitters must work with signals in a narrow range of operating frequencies. This range of operating frequencies is typically between 20 Hz and 200 Hz. This limits the designers to this narrow range of operating frequencies. Furthermore, the narrow range of operating frequencies makes it impossible to use a conventional transmitter with some flowmeters, such as straight tube flowmeters, which operate in a higher frequency range of 300-800 Hz. Straight tube flowmeters operating at 300-800 Hz tend to exhibit smaller sensitivity to Coriolis effects used to measure mass flow rate. Therefore, a finer measurement of the phase difference between sensors is-needed to calculate mass flow rate. In order to use one type of transmitter on several different designs of Coriolis flowmeters operating at several different frequencies, manufacturers of Coriolis flowmeter have found that it is desirable to use a digital signal processor to generate the drive signals and process the signals received from the pick-off sensors. A digital signal processor is desirable because the higher demand in measurement resolution and accuracy put on analog electronic components by flowmeters operating at higher frequencies, such as straight tube designs, are avoided by the digitalization of signals from the pick-offs as the signals are received by the transmitter. Furthermore, the instructions for signaling processes used a digital processor may be modified to operate on several different frequencies. However, digital signal processors have several disadvantages as compared to conventional analog circuit transmitters. A first problem with a digital signal processor is that digital processors are more expensive to produce because the circuitry is more complex. Secondly, digital signal processors require a circuit board having a greater surface area which can cause problems when space is at a premium in a flowmeter design. Thirdly, digital signal processors require more power to operate than analog circuits. Power consumption is especially a problem when a processor must operate at a maximum clock rate in order to provide all the computations needed to process the signals and generate a material property measurement, such as mass flow. For all of these reasons, there is a need in the art for a digital signal processor that is adaptable across several flowmeter designs, that is inexpensive to produce and reduces the amount of power needed to perform the needed computations. The above and other problems are solved and an advance in the art is made by the provision of a multi-rate digital signal processor of the present invention. The present invention is comprised of processes that are stored in a memory and executed by the processor in order to process the signals received from pick-offs on a vibrating conduit. The processes of this invention offer many advantages that make it viable to use a single type of digital signal processor in many types of Coriolis flowmeters. A first advantage of the processes of the present invention is that the processes do not lose accuracy in spite of using finite arithmetic in lieu of floating point arithmetic. A second advantage of the processes of the present invention is that the processes can be implemented on any number of low cost, low power digital signal processors such the Texas Instruments TM3205xx, Analog Devices ADSP21xx, or Motorola 5306x. The instructions for the processes of the present invention are small enough to reside in the internal memory of a digital signal processor which eliminates the need for fast access external memory which increases the cost, power consumption and board space for the transmitter. The processes have a small number of computational constructs which improves the portability of the processes between low cost processors. A third advantage is that the computational requirement of the processes is minimized. This reduction in the computational requirement allows the digital signal processor to run at a clock rate lower than the maximum clock rate of the processor which reduces the power consumption of the processor. A transmitter that performs the processes of the present invention has the following electronic components. Analog signals from the pick-offs attached to the sensors are received by an Analog to Digital (“A/D”) converter. The converted digital signals are applied to a standard digital processor. The digital processor is a processing unit that executes machine readable instructions that are stored in a memory connected to the processor via a bus. A typical digital processor has a Read Only Memory (ROM) which stores the instructions for performing desired processes such as the processes of the present invention. The processor is also connected to a Random Access Memory which stores the instructions for a process that is currently being executed and the data needed to perform the process. The processor may also generate drive signals for the Coriolis flowmeter. In order to apply the drive signal to a drive system, a digital processor may be connected to a Digital to Analog (D/A) convertor which receives digital signals from the processor and applies analog signals to the drive system. The processes of the present invention perform the following functions to determine the frequencies of the signals received from the pick-off sensors as well as the phase difference between the signals. First, the signals are received from the pick off sensor at a first sample rate. A sample rate is the amount of inputs received from the pick-offs that are used to characterize the signals from the pick-offs. The signals are then decimated from a first sample rate to a desired sample rate. Decimation is simply converting from a first number of samples to a lesser number of samples. Decimation is performed to increase the resolution of the signals sampled to provide a more precise calculation of signal frequency for each signal. The frequency of each signal is then determined. In order to use the same processes with different flowmeters having different frequencies, the following steps may also be performed. An estimate of the oscillation frequency of the flowmeter is calculated. The estimated frequency is then used to demodulate the signals from each pick-off into an I component and a Q component. The I component and the Q component are then used to translate the signals to a center frequency if the operating frequency of the signals is greater than a transition frequency. After demodulation, the signals may be decimated a second time to improve the resolution of the signals a second time. The dominant frequency of the signals is then isolated and precisely measured. The translation to a zero frequency is then calculated for both the I component and Q components of the signals. At this time, each component may decimated again to improve the accuracy of measurement. The frequency band of each signal can be narrowed as much as desired by appropriate low pass filtering at this time. A complex correlation is then performed which determines the phase difference between the signals. The above process allows a low power, low cost, digital processor to be used in a different types of Coriolis flowmeter which operate over a wide range of operating frequencies. The present invention can be understood from the following detailed description and the following drawings: FIG. 1 illustrating a Coriolis Flowmeter having a digital transmitter that performs multi-rate pick-off signal processes of this invention; FIG. 2 illustrating a block diagram of a digital signal transmitter; FIG. 3 illustrating a flow diagram of the operations performed by a digital transmitter; FIG. 4 illustrating a flow diagram a process for generating data from signals received from pick-off sensors; FIG. 5 illustrating a process for performing a decimation of signal samples from a pick-off; FIG. 6 illustrating a process of calculating an estimated frequency of the signals received from the pick-offs; FIG. 7 illustrating a process for performing a high-low frequency selection for the received signals; FIG. 8 illustrating a process for demodulating the received signals; and FIG. 9 illustrating a method for determining data about flow tube vibration from the received signals. Coriolis Flowmeter in General—FIG. 1 FIG. 1 shows a Coriolis flowmeter Meter assembly When flowmeter Conduits Conduits Transmitter It is known to those skilled in the art that Coriolis flowmeter A Digital Transmitter FIG. Driver signals are transmitted over path Processing unit Overview of Operation Performed by Digital Transmitter FIG. 3 is an overview of the functions performed by digital transmitter A Process for Generating Data About the Pick-off Signals in Accordance with the Present Invention—FIG. FIG. 4 illustrates process Process In step After the second decimation in step A Process for Decimating Sample Rates of Signals from Pick-offs-FIG. 5 FIG. 5 illustrates a process for decimating the rate of samples received from pick-offs. The same process is used for the decimation performed in each of steps A decimation as described in process
Where: A,B,C,D=matrices representing the state of the system; x u y From induction, it is clear that: When decimating a signal by a factor of M, only every M-th sample is going to be kept. Therefore, all but the last output row of the above matrix can be eliminated to yield the following equation: From the above, it is obvious that the number of accumulate/multiply operations for one recursion of the above equation is:
where: N N=order of the matrix A; and M=the block size which is equal to the decimation rate of the process. Therefore, the computational load for performing the decimation is
where: R F The memory needed to perform a decimation is as follows: memory to store each filter coefficient which may be read-only (ROM); memory to store the filter state vector x an input block buffer memory (read-write). FIG. 5 illustrates the process of decimation using the above block processing method. Process A Process for Estimating the Frequency of the Received Signals FIG. Process The process Process where: F ω F A Process for a High-Low Frequency Selector—FIG. 8 Process
where: F From this equation, it is apparent that the process for determining frequency is not accurate when the sample rate is 4 kHz and the frequency of the signal measured is as low as 20 Hz. Process If the actual estimated frequency is less than the reference frequency, an estimated frequency of zero is returned. If the actual estimated frequency is greater than the reference frequency, the estimated frequency is calculated to be the actual estimated frequency minus 120 Hz. A Process for Demodulating the Received Signals—FIG. 7 FIG. 7 illustrates a process This process uses the estimated frequency that was either calculated in process
where: ω F F The real valued ‘twiddle’ factor is calculated in step
with
where β=receivedsignalftomeither oneofthepick—offsensors. The dot product of the ‘twiddle factor’ and the actual received signal is calculated in step
It should be noted that if process
However, this can be remedied by a dual decimation as described below. The first component corresponding to the − in the above equation is the signal of interest. The second signal corresponding to the + sign in the equation will be filtered out in the next decimation process in step Process for Generating Data from the Received Signals—FIG. 9 FIG. 9 illustrates a process where α<1 is a convergence parameter adjusting the bandwidth of the filter and a
The zero points of H (z) are given by the equation:
where z=zero points; j=a constant; and ω=signal. Therefore, poles of the signals are expressed in the following equation:
In step In step
where F a
where ω F As noted above the received signals can be shown as: x From the above equations, the output of the quadrature demodulation is:
In order to further increase the signal resolution, a decimation is performed in step
After the decimation is performed, a phase difference of the signals is performed in step
Then, the signal is multiplied with the second signal to perform a complex correlation between the pick-off signals as shown in the following equation:
Therefore, the phase difference is given by the following equation:
The phase difference can then be used to calculate mass flow rate and other properties of the material flowing through the material. The above is a description of a digital transmitter Patent Citations
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